Memetic algorithm with Preferential Local Search using adaptive weights for multi-objective optimization problems

Evolutionary multi-objective optimization algorithms are generally employed to generate Pareto optimal solutions by exploring the search space. To enhance the performance, exploration by global search can be complemented with exploitation by combining it with local search. In this paper, we address the issues in integrating local search with global search such as: how to select individuals for local search; how deep the local search is performed; how to combine multiple objectives into single objective for local search. We introduce a Preferential Local Search mechanism to fine tune the global optimal solutions further and an adaptive weight mechanism for combining multi-objectives together. These ideas have been integrated into NSGA-II to arrive at a new memetic algorithm for solving multi-objective optimization problems. The proposed algorithm has been applied on a set of constrained and unconstrained multi-objective benchmark test suite. The performance was analyzed by computing different metrics such as Generational distance, Spread, Max spread, and HyperVolume Ratio for the test suite functions. Statistical test applied on the results obtained suggests that the proposed algorithm outperforms the state-of-art multi-objective algorithms like NSGA-II and SPEA2. To study the performance of our algorithm on a real-world application, Economic Emission Load Dispatch was also taken up for validation. The performance was studied with the help of measures such as Hypervolume and Set Coverage Metrics. Experimental results substantiate that our algorithm has the capability to solve real-world problems like Economic Emission Load Dispatch and is able to produce better solutions, when compared with NSGA-II, SPEA2, and traditional memetic algorithms with fixed local search steps.     

Drain Current Modeling of Tunnel FET using Simpson’s Rule

Silicon - Tunnel Field Effect Transistor can be introduced as an emerging alternate to MOSFET which is energy efficient and can be used in low power applications. Due to the challenge involved in...     

Fixed bed column study for heavy metal removal using phosphate treated rice husk

This paper reports the results of the study on the performance of low-cost adsorbent such as raw rice husk (RRH) and phosphate treated rice husk (PRH) in removing the heavy metals such as lead, copper, zinc and manganese. The adsorbent materials adopted were found to be an efficient media for the removal of heavy metals in continuous mode using fixed bed column. The column studies were conducted with 10 mg/l of individual and combined metal solution with a flow rate of 20 ml/min with different bed depths such as 10, 20 and 30 cm. The breakthrough time was also found to increase from 1.3 to 3.5 h for Pb(II), 4.0 to 9.0 h for Cu(II), 12.5 to 25.4h for Zn(II) and 3.0 to 11.3 h for Mn(II) with increase in bed height from 10 to 30 cm for PRH. Different column design parameters like depth of exchange zone, adsorption rate, adsorption capacity, etc. were calculated. It is found that the adsorption capacity and adsorption rate constant were increased and the minimum column bed depth required was reduced when the rice husk is treated with phosphate, when compared with that of RRH.     

Spirulina platensis‐capped mesoporous magnetic nanoparticles for the adsorptive removal of chromium

The magnetic nanoparticles prepared through the co‐precipitation method were surface modified using Spirulina platensis. The mesoporous and superparamagnetic nature of the adsorbent was confirmed by Brunauer‐Emmett‐Teller (BET) and vibrating sample magnetometer (VSM) analyses, respectively. Further, an increased specific surface area of 75.3 m²/g was reported in the BET studies. Parameters such as pH, contact time, concentration, and temperature were studied to optimize the operating conditions influencing adsorption. Thermodynamic studies justified the spontaneity and endothermic nature of adsorption. The adsorbent exhibited a better performance at 1.5 pH and 120 minutes of contact time. The monolayer adsorption capacity of the material was found to be 29.23 mg/g from the evaluation of Langmuir adsorption isotherm. The second‐ order kinetic studies suggest the predominance of chemisorption. Further, the X‐ray photoelectron spectroscopy (XPS) studies confirmed that the adsorption mechanism is electrostatic attraction accompanied by reduction. Notably, a regeneration efficiency of 75.26% was achieved with NaOH as the desorbing agent.     

Novel report on single phase BiFeO<Subscript>3</Subscript> nanorod layer synthesised rapidly by novel hot-wall spray pyrolysis system: evidence of high magnetization due to surface spins

This is the novel report on the rapid synthesis of single phase BiFeO₃ nanorods by novel hot wall assisted spray pyrolysis system. The deposition has been carried out in an indigenously fabricated system and the entire process is completed in 4 s time duration. The structural, morphological, optical and magnetic properties of BiFeO₃ nanorods have been studied in the work. The mechanism of growth of BiFeO₃ nanorods has been explained extensively. The magnetic studies carried out with SQUID-VSM results BiFeO₃ nanorods showing higher saturated magnetization in comparing with previous reports.     

Low-temperature acidic amylases from Aspergillus for desizing of cotton fabrics

The patterns of degradation occurring when textile fabrics are treated with sulphuric acid are derived from the change in tensile strength at different concentrations. Characteristic shapes differ for different fibre types and range from a near-linear mode to one in which a high initial loss of property takes place.

Results show a general tendency, with individual variations, for deterioration to increase with time and concentration, molecular and structural factors presumably being responsible.     

Structure-Based Virtual Screening Reveals Ibrutinib and Zanubrutinib as Potential Repurposed Drugs against COVID-19

Coronavirus disease (COVID)-19 is the leading global health threat to date caused by a severe acute respiratory syndrome coronavirus (SARS-CoV-2). Recent clinical trials reported that the use of Bruton’s tyrosine kinase (BTK) inhibitors to treat COVID-19 patients could reduce dyspnea and hypoxia, thromboinflammation, hypercoagulability and improve oxygenation. However, the mechanism of action remains unclear. Thus, this study employs structure-based virtual screening (SBVS) to repurpose BTK inhibitors acalabrutinib, dasatinib, evobrutinib, fostamatinib, ibrutinib, inositol 1,3,4,5-tetrakisphosphate, spebrutinib, XL418 and zanubrutinib against SARS-CoV-2. Molecular docking is conducted with BTK inhibitors against structural and nonstructural proteins of SARS-CoV-2 and host targets (ACE2, TMPRSS2 and BTK). Molecular mechanics-generalized Born surface area (MM/GBSA) calculations and molecular dynamics (MD) simulations are then carried out on the selected complexes with high binding energy. Ibrutinib and zanubrutinib are found to be the most potent of the drugs screened based on the results of computational studies. Results further show that ibrutinib and zanubrutinib could exploit different mechanisms at the viral entry and replication stage and could be repurposed as potential inhibitors of SARS-CoV-2 pathogenesis.     

Honey derivatized Au and Ag nanoparticles and evaluation of its antimicrobial activity

Biomolecules hosting the synthesis of nanoparticles has achieved considerable attention in recent decades due to their abundant availability, excellent biocompatibility and low toxicity. The present study demonstrates a rapid, cost-effective and eco-friendly fabrication of gold and silver nanoparticles at room temperature using natural honey as a source of stabilizing and reducing agent. The nanoparticles obtained were unambiguously characterized by using various characterization techniques such as transmission electron microscopy (TEM), UV-Visible absorption spectroscopy, X-ray diffraction and energy dispersive (EDX) X-ray analysis. The average size of Au and Ag nanoparticles are 10 and 12 nm respectively. Ag nanoparticles capped by honey exhibited superior antimicrobial activity while Au nanoparticles revealed passable activity against pathogenic bacteria and Candida albicans, including multi-resistant strains for the first time.